It is desirable to predict near range communications quality for various reasons. For example, it is useful to model the range of publically available Wifi™ hot spots and telecommunications transmitters. Also, it can be important to assess the signal strengths and viability of communications within cluttered urban environments, e.g. to aid frequency/channel assignment for public service (Health Services, Police, Fire brigade) communications and local citizen band radio (taxi firms, etc). Such prediction can be particularly difficult in cluttered and complex (for example, urban) environments where a large number and variety of objects and conditions, such as traffic levels, can affect communications quality.
Known techniques for accurate communications propagation modelling include ray tracing, which is time consuming and computationally expensive. Other techniques, such as purely diffraction-based methods, are faster but do not have the same level of accuracy and do not take into account detailed features such as traffic levels, etc.
A large number of existing proprietary and open source models/maps of environments are available. However, no known single data source is available in a readily-useable format that contains all the various types of information that can provide accurate propagation modelling.